Second Academic Libraries RDS Follow-Up/LIBER Data Set Guide

This guide covers both the LIBER_RDS_Cleaned_LQ_dataset (SAV), and the LIBER_RDS_Cleaned_LQ_convert_dataset (CSV). Both hold the same data on the Academic Libraries Second Follow-Up, but are provided for convenience/options/preferences to the user. 



Authors: 

Carol Tenopir, University of Tennessee 
Sanna Talja, University of Tampere 

Wolfram Horstmann, University of Gottingen 
Elina Late, University of Tampere 

Dane Hughes, University of Tennessee 

Danielle Pollock, University of Tennessee 

Birgit Schmidt, University of Gottingen 

Lynn Baird, University of Idaho 

Robert J. Sandusky, University of Illinois at Chicago 

Suzie Allard, University of Tennessee



Key words associated with the dataset: 
Research Data Services; data management; academic libraries



Note: Research Data Services is abbreviated to RDS in the dataset, as found in some values




Notes about the data set:

The survey instrument found accompanied with the data sets (which has been submitted along with a manuscript on our findings was submitted to LIBER Quarterly on Oct. 17th, 2016) should prove helpful navigating the questions, variables, and values.


V1 represents a unique identifier for the responses.


Q1 is the beginning of the survey questions and variables in the data set, as well as responses to the questions, and follows the format of the survey instrument accompanied with the data set, as well as found in the appendix of the article (e.g. Q1 in data set matches Q1 in survey instrument, Q2 in data set matches Q2 in survey instrument, etc.). There are instances where a question has multiple items associated with it, and in these cases, the data set provides them with a number. For example, Q3 has 5 items, and in the data set is named Q3_1, Q3_2, etc. 

Within the data set, there are groups of recoded variables that match the original variable (e.g. Q3_1 and Q3_1_Recode). The purpose of recoding was to condense the "no, but plan to" and level of agreement values into one category for crosstab analysis, as well as for visual data representation purposes.

The OpenAIRE_Region variable was used to analyze responses by region.